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  2. Type inference - Wikipedia

    en.wikipedia.org/wiki/Type_inference

    The origin of this algorithm is the type inference algorithm for the simply typed lambda calculus that was devised by Haskell Curry and Robert Feys in 1958. [citation needed] In 1969 J. Roger Hindley extended this work and proved that their algorithm always inferred the most general type.

  3. Stan (software) - Wikipedia

    en.wikipedia.org/wiki/Stan_(software)

    Variational inference algorithms: Automatic Differentiation Variational Inference [7] Pathfinder: Parallel quasi-Newton variational inference [8] Optimization algorithms: Limited-memory BFGS (Stan's default optimization algorithm) Broyden–Fletcher–Goldfarb–Shanno algorithm

  4. Backward chaining - Wikipedia

    en.wikipedia.org/wiki/Backward_chaining

    With backward reasoning, an inference engine can determine whether Fritz is green in four steps. To start, the query is phrased as a goal assertion that is to be proven: "Fritz is green". 1. Fritz is substituted for X in rule #3 to see if its consequent matches the goal, so rule #3 becomes: If Fritz is a frog – Then Fritz is green

  5. Semantic reasoner - Wikipedia

    en.wikipedia.org/wiki/Semantic_reasoner

    Drools, a forward-chaining inference-based rules engine which uses an enhanced implementation of the Rete algorithm. Evrete, a forward-chaining Java rule engine that uses the Rete algorithm and is compliant with the Java Rule Engine API (JSR 94). D3web, a platform for knowledge-based systems (expert systems).

  6. Automated reasoning - Wikipedia

    en.wikipedia.org/wiki/Automated_reasoning

    John Pollock's OSCAR system [2] is an example of an automated argumentation system that is more specific than being just an automated theorem prover. Tools and techniques of automated reasoning include the classical logics and calculi, fuzzy logic, Bayesian inference, reasoning with maximal entropy and many less formal ad hoc techniques.

  7. Hindley–Milner type system - Wikipedia

    en.wikipedia.org/wiki/Hindley–Milner_type_system

    [3] [4] Among HM's more notable properties are its completeness and its ability to infer the most general type of a given program without programmer-supplied type annotations or other hints. Algorithm W is an efficient type inference method in practice and has been successfully applied on large code bases, although it has a high theoretical ...

  8. Inference engine - Wikipedia

    en.wikipedia.org/wiki/Inference_engine

    The inference engine applied logical rules to the knowledge base and deduced new knowledge. This process would iterate as each new fact in the knowledge base could trigger additional rules in the inference engine. Inference engines work primarily in one of two modes either special rule or facts: forward chaining and backward chaining. Forward ...

  9. Obliq - Wikipedia

    en.wikipedia.org/wiki/Obliq

    A type inference algorithm for record concatenation, subtyping, and recursive types has been developed for Obliq. Further, it has been proved to be NP-complete [1] and its lowest complexity to be Ο(n 3) or if under other modeling up to certain conditions down to Ο(n 2) [2] and its best known implementation runs in Ο(n 5).